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Machine Learning · Practical ML
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Aurélien Géron · 3rd edition · 2022
💎 PremiumIntermediate★★★★★856 pagesISBN 978-1098125974
The most popular ML book worldwide. Covers classical ML and deep learning with practical code examples and real datasets.
Why you should read this
If you can only read ONE ML book, choose this one. It takes you from zero to deploying production ML models.
If you can only read ONE ML book, choose this one. It takes you from zero to deploying production ML models.
Key Topics
Chapters (10)
1The ML Landscape12 key concepts
What is ML, types, challenges, workflow
2End-to-End ML Project16 key concepts
California housing price prediction pipeline
3Classification14 key concepts
Binary, multiclass, confusion matrix, ROC
4Training Models18 key concepts
Gradient descent, polynomial regression, regularization
5SVMs10 key concepts
Linear and kernel SVMs, margin maximization
6Decision Trees8 key concepts
CART, Gini, entropy, pruning
7Ensemble Methods14 key concepts
Random forests, boosting, bagging, stacking
8Dimensionality Reduction10 key concepts
PCA, t-SNE, UMAP, LLE
9Introduction to Neural Networks16 key concepts
Perceptrons, backpropagation, Keras API
10Deep Computer Vision (CNNs)18 key concepts
Convolutional layers, transfer learning, object detection
Real-World Applications
- House price prediction
- Image classification
- Sentiment analysis
- Recommendation systems
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